Systems for archiving transaction data and image data generated by check processing operations performed by financial institutions are well known. By transaction data, we mean not only the information encoded on the check itself, magnetically or otherwise, but also the information about the capture process and the handling of the item subsequent to the capture process. Image data, of course, refers to an image of the check itself, or other financial document of which an image is captured.
Typically, such archive systems are based on relational database management systems such as DBII, Oracle or Informix. Large and even medium size financial institutions can process hundreds of thousands, if not millions, of checks (or items) in a single day. The information captured must be stored for several years so that information relating to an item can be retrieved in connection with various banking operations, such as retail customer service or treasury or cash management services for commercial customers. The costs associated with storing such a large volume of information are very high. Thus, there is a need for a system that provides cost effective, long-term storage of transaction data and image data generated in connection with the item capture process.
As discussed above, financial institutions generate vast amounts of transaction data and image data in connection with check or item processing. Item research as it relates to retrieving such transaction and image data for use by retail or commercial customers of the financial institution, as well as operational personnel, usually to determine the occurrence or non-occurrence of certain events, such as presentment, payment or clearance of an item.
Item research that is executed at multiple financial institution locations and performed across multiple systems is time and resource intensive. Items are typically captured on at least two different capture platforms (e.g., Check Processing Control System and ImageMark) and capture sites are typically dispersed geographically. As a result, substantial human resources are required to research items because multiple systems need to be accessed. In addition, the amount of time to research an item and deliver a hardcopy (e.g., microfilm-based copy) of the item can take hours and even days. Moreover, historical information on these disparate systems is limited. This drain on resources ultimately results in poor customer service.
Previously available commercial systems, e.g., the Vector 11 System available from Sterling Commerce of Columbus, Ohio, receive all items from the Check Processing Control System (“CPCS”) and sort them by a sequence number. There are no interfaces to direct deposit account (“DDA”) or cash letter systems. Items cannot be extracted by entry, block or batch. Entry, block and batch summarization is also not supported. The Vector 11 System uses a Customer Information Control System (“CICS”) interface, but does not support a callable interface that can be accessed through a variety of host and PC application development languages. Thus, there is a need for an archive system that provides an integrated, efficient and quick item research system.